Welcome to the Metastructure: The New Internet of Transportation

520 DESIGN

Though I haven’t lived there for nearly three decades, I still consider myself a citizen of Los Angeles. Soy un Angeleño. That means, among other things, I drive. For me, a car is like a suit or a good exoskeleton. Road trips, going 100 miles per hour on a freeway, racing through Park La Brea—they’re all sewn as tightly into my DNA as ice-skating in Central Park is for a New Yorker.

Despite that heritage, I’ve been running an experiment on myself and my hometown. My last three trips there, I didn’t rent a car; it’s been nothing but taxis, Uber, and one time I borrowed my dad’s. (He still identifies as an Angeleño too, though he lives in Tarzana. Which … come on.) Point is, it worked. Not only did I move through space and time every bit as efficiently—more, if you believe that screwing around on Twitter and email is useful—I took new routes. I got everywhere I needed to go, faster than I otherwise would have, without worrying once about getting lost, finding parking, or maybe having had one last drink.

It’s starting to seem like everyone is running some version of my experiment. Driving itself is changing. Between electric and self-­driving vehicles, ubiquitous sensors, network connectivity, and new kinds of transportation companies, everything is in flux: cars, how we feel about them, even roads and cities. This isn’t just hypothetical; you can use these things today. A radical phase shift is redrawing the map, literally and metaphorically.

It’s a shift we need. The fact is, too many people own too many cars—an estimated 1.2 billion vehicles globally. Congestion in many cities is already untenable, and it’s only getting worse. And the existence of so many cars is both environmentally disastrous and reliably lethal (to the tune of more than 32,000 driving deaths a year in the US). If current trends hold and places like China and India make personal vehicle ownership a hallmark of middle-class achievement like the US has, the number of vehicles goes up to 2 billion by 2040.

Being chauffeured around L.A. by Ubers knocked a couple days off my death clock from reduced stress.

Of course, engineers, designers, and planners have been trying to improve urban transportation for decades. Their schemes have included everything from city­wide operations centers that optimize traffic signals to increased public transportation to high-density housing near train and metro lines. But these solutions have always been top-down: They rely on centralization, bureaucracy, and control. And they don’t work.

Individually, the new tools and technologies for moving around are interesting; put them together and you get something profound. Connect these new systems and individual networks to each other and they self-­assemble into a transportation super-­network. It’s decentralized, offers multiple routes from node to node, carries any kind of person or thing to any kind of place, and adjusts itself in real time.

Sound familiar? Of course it does. That’s how the Internet works. (Remember when it was called the information superhighway? It’s like that, but for actual highways.) This decentralized approach to remapping our physical roads is fundamentally (and finally) changing everything about how we get around. Bus, train, ferry, Lyft, self-­driving car, hyperloop, or a combination of all of these things—it doesn’t matter. Think of it this way: To the new transportation supernetwork, you and I are just data. It doesn’t matter where we want to go; it just knows how to get us there—faster, cheaper, and utterly in control.

Mountain View is a suburban hellscape.

I don’t mean it’s not a nice place. The streets are lined with trees, the buildings are just a couple of stories tall, and the roads are reassuringly rectilinear. But wow, is it an ocean of parking lots, dotted by an archipelago of office buildings. So seeing the Mountain View hellscape through the windows of a robot car is even stranger than it sounds. Google, as you’ve heard, is working on a fully autonomous vehicle—“level 4,” according to the National Highway Traffic Safety Administration. (Your dumb car that you have to, like, drive is level 0.)

This future has a history. General Motors’ Futurama exhibit at the 1939 World’s Fair, harbinger of modernity, touted broad highways and self-driving cars. Transit engineers have advocated for personal, on-demand pods since at least the 1960s. But the developers of so-called Intelligent Vehicle Highway Systems didn’t predict that the primary intelligence would reside in the cars instead of a control tower. And they didn’t know that people would carry GPS-equipped supercomputers in their pockets.

The size and shape of a city, the literature says, is limited to the range someone can travel in 45 minutes to an hour. If you’re on foot, that’s compact, downtown-sized. In the early 20th century, streetcars allowed people to range farther within the time limit, leading to suburbs. It was a phase transition. The new highways of the mid-20th century brought a second phase shift, gutting downtowns and creating a schism between privately owned cars for the relatively wealthy and public transit for the not-so-much.

Today’s emerging transportation network represents a third phase transition. And ground zero for that shift is in Mountain View. Google X, headquarters for the company’s maddest science, has built two dozen self-­driving pods that look like something out of Richard Scarry. For reporters, the publicity crew will set up a ride in a Lidar- and camera-studded self-driving Lexus SUV. One Googler rests her hands lightly on a steering wheel that rotates by itself; another, riding shotgun, watches a laptop screen and a jury-rigged display in the dashboard. I sit in back.

As we cruise the streets around ­Google X, the robot’s brain thinks it is moving through a Borgesian 3-D map of the same space, depicted on the laptop. It’s a Matrix populated by irregular polyhedra out of a vector-mapped 1980s arcade game—see-through blocks representing other cars (purple), cyclists (red), and people (yellow).

Every so often one of them does something unexpected—a purple car-block moves in a surprising way, or a yellow pedestrian-cube looks poised to jaywalk. The Lexus stops suddenly enough to strain the seat belts. “We make the cars as paranoid as possible,” says Chris Urmson, the project lead for self-driving cars at Google, “because there are some things they won’t be able to avoid.”

520 DESIGN

Google isn’t the only company building robot cars, of course. Six major automakers (and Tesla) have announced plans to build varying levels of autonomy into their products. If they succeed and the roads fill with robots, that paranoia Urmson is embedding in his code could mean the end of car crashes. Combine that with the end of internal combustion, and cars will change shape. No more crumple zones, airbags, or steel slabs for doors. You get something more like one of Google’s cute little pods, with a center console for controls and little else inside, leaving room for bags and kids’ car seats in a vehicle the size of a golf cart. Or maybe it looks like a Tesla Model S, a sleek sedan with seven seats and front and rear trunks.

It could also mean the end of congestion. When you’re stuck in stop-and-go, you think of yourself as a driver and everyone else as traffic. But the fact is, we’re all in it together. Too many cars on poorly maintained roads built for a fraction of the volume clog like a crudded-up sewage pipe. And building more roads won’t help; it just encourages more people to drive. That’s called “induced demand.” Traffic engineers understand it as well as the weather—and can do just as much about it. All that traffic costs 3 billion gallons of fuel and 7 billion hours of time. In 2014, that added up to $160 billion.

But given the right conditions, nothing stops an armada of robot cars from driving 100 miles an hour with 6 inches of headway between them. Notionally, this kind of coordination avoids induced demand too. In other words: the end of traffic.

But that’s not even the interesting part.

The first example of high-utilization autonomous driving was the New York taxicab,” says Dan Ammann, president of General Motors. “Uber improved on that. From a customer’s point of view, that’s also an autonomous experience.” So yes, the president of GM acknowledges that a driving excursion other than top-down, wind-in-hair, open-road, American-muscle-car-roar-competing-with-Steely-Dan might still be fulfilling.

Or try this one: “If you think we’re going to shove two cars in every garage in Mumbai, you’re crazy,” says Bill Ford, executive chair of Ford Motor Company. “Unless we figure out a very different urban transportation model, it’s not going to work.” Says the great-­grandson of the man who figured out how to put two cars in every garage.

Ammann, Ford, and their fellow bosses in the car business have begun to embrace “mobility”—that is to say, using decentralized data to integrate every mode of transportation. By providing on-demand access to a car you don’t have to drive or park, Uber, Lyft, and other private transportation network companies (as transit nerds call them) are modeling a future for autonomous cars. This is where you can begin to see the phase transition, like the first signs of order forming around a seed of crystal.

Drivers are as solvable a computational problem on the road as bits are on the Internet.

Getting chauffeured around Los Angeles felt like it knocked a couple days off my death clock from reduced stress alone. Even the most complicated work trip was easy: I guided my taxi from the Burbank airport to the residential street where my hotel was hiding in West Hollywood with Waze. A few days later I used Uber for a day of reporting—West Hollywood to Venice. Then I got another Uber back to the hotel to collect my stuff while the driver waited. Then out to Burbank to see people at Disney. I walked out of the studio while a line of employee cars crept past the gatehouse, and a last Uber picked me up and took me back to the airport. It was the most stress-free day of traversing a large American city I’ve ever had. Total cost: $197.09. Cost to rent and park a car for those same days: nearly $500.

As a packet of moving-thing, I wasn’t particularly aware of the make or model of the cars I rode in. Very un-Angeleño of me. But I spent a good chunk of every trip with my nose pointed at my phone, watching a route and map unspool around me. I was watching the network happen.

In 1960, Kevin Lynch, an urban planning professor at MIT, sent his students to interview people about their cities. The resulting book, The Image of the City, identified five features that people almost always saw: paths, the routes they took habitually; edges, the places beyond which they had no idea about; districts, where they knew their way around; nodes, like “home” or “work”; and landmarks. Without knowing it, Lynch was describing a city as a network—but an inefficient one. The packets never varied their routes, hugging the same paths and nodes. Sure, they might glance wistfully at a tower—an Eiffel or a Sears—as they chugged home, but they never wondered what was on the other side of the park or behind that brutalist mall.

To paraphrase digital activist John Gil­more, autonomous vehicles, powered by smartphones and sensors and the Internet, interpret those limitations as damage and route around them—just like the Internet. The Lynchian edges crack open. Drivers are as solvable a computational problem on the road as bits are on the Internet, moving from node to node in the most efficient way.

An amazing thing happens when that information gets freed: The city opens up. Angeleños have begun complaining that once-quiet streets have become throughways connecting one boulevard to another, but for me, cruising along streets that didn’t exist in my mental map was like finding a new city hidden inside my hometown. “Users believe they have a bigger city,” says Di-Ann Eisnor, director of growth at Waze. “It expands. Like, ‘Hey, this is all my city.’”

What all these services and partnerships are building isn’t infrastructure. Let’s call it metastructure. It’s an evolving map of spacetime that robot cars and buses and trolleys and bikes live in, constantly updated, always available. London cabbies famously have to acquire the Knowledge, a preternatural understanding of not just the city’s streets but their ebbs and flows in time. Make that into something a robot can learn and a phone can access, and you have metastructure.

If it works, everything changes: fewer cars on the road, never getting into accidents, never needing a parking space. You’ll ride in a car, but you’ll never own one.

Today, cars are people’s second-largest household expenditure, and they sit unused 23 hours a day. When they’re on the road, some vast proportion of them are looking for parking; an average of 30 percent of all cars in any urban downtown are cruising for a space—wasting time, worsening congestion, and adding to vehicle-miles traveled. “If someone described that model to you and didn’t tell you it was cars, you’d say it was ripe for disruption,” GM’s Ammann says. A 2015 study of Lisbon, Portugal, by the Organisation for Economic Cooperation and Development found that a fleet of just 26,000 TaxiBots—hypothetical on-demand, autonomous carpool vehicles—could replace every one of the city’s 203,000 cars. Think about that: the same population, 565,000 people, served by a tenth the number of cars.

Let’s get even weirder: Given their constrained rule sets and shared behaviors, those little pods are going to start flocking. When a police car comes screaming down the road, blasting vehicle-to-vehicle RF to get the Google pods to move, the robots are going to swirl like a school of anchovies trying to evade a swordfish.

When you don’t need parking anymore, you don’t need parking lots or curbside parking or valets or enforcement officers. “I’m standing in a huge parking lot here at the airport,” says Susan Shaheen, a transportation researcher at UC Berkeley, when I catch her on her mobile phone. “It’s a giant sea of cars. I can’t even see the end of it. What could you do if you didn’t need that? This could be housing. It could be a school, a playground, a garden.”

Robo-cars will swarm: when the police come screaming down the road, they’ll swirl out of the way like a school of anchovies.

Just in time, too. The metastructure is changing how people live. In a historic reversal, more people want to live in cities than outside them. Car ownership is declining. Depending on which statistics you believe, vehicle-miles traveled—a classic transportation metric—is on the decline. Transit rider­ship is up. Cities and states are building new subways, trolleys, even high-speed rail lines. NIMBYism and densification are still at war, but, hey, at least it’s a real fight. “Instead of just a single mode to get you from A to B, you put together optimal route planning,” says Ashley Hand, a transportation technology strategist for the City of Los Angeles. “Walk to this, carpool here. We hope to see the integration of all these services.” The data on all of that will be richer, smarter, and more available. The transportation system of the future builds the city of the future.

Unless it’s a road to dystopia. If increased mobility extends the 45-minute range just as millennials start needing to buy car seats—and as housing costs in downtowns keep going up—maybe they all move even farther into suburbs and exurbs. Their cars will be robots, but that could just lead to more sprawl. More streets, more highways, all filled with empty pods running errands for people before taking them home to undifferentiated exurban foam. “You could imagine all this technology pulverizing our cities, and then it would all look like Florida,” says Luis Bettencourt, a researcher at the Santa Fe Institute who studies cities.

Worse, the two-tier system that already exists—cars versus public transit—could become even more exaggerated. People with money and credit cards get Uber and Google buses and can live downtown; ­people without economic resources get trapped in transportation deserts in the exurbs or in cities that roll up their streets at 7 pm. Baseline-level, barely maintained transit further marginalizes current users instead of attracting new ones.

None of that has to happen. The metastructure can’t be something available only to people with credit cards. The digital network led to smartphones—toys of the rich at first, but eventually (owing to their utility) reaching saturation levels. Everything that moves us, from shared bicycles to hyperloops and rockets, gets better with more nodes, more routes. That’s what networks do. “We have to start designing for this disruption,” Shaheen says. “Ultimately a building is connected to a car or vehicle services, to the human being, the water supply, the food supply. Everything becomes a dynamic, evolving, almost living system.”

The truth is, whatever we fear about these changes, the car ownership model that has dominated the past 65 years isn’t sustainable. We can’t just keep building more roads. That only leads to more cars, more highways, more traffic, more big-box malls and exurban sprawl, and more of us trying to distract ourselves from it all with podcasts.

A few weeks ago I saw a video of a test trolley rolling into a brand-new station at Santa Monica State Beach. I grew up driving there, exulting in the moment that the 10 freeway (direct article in front of highway number = Angeleño) exits a short underpass, and the Pacific, crackling blue under a SoCal sun, opens up and out in front of the roadway. But I can imagine finding my way there via the metastructure, without ever touching a steering wheel, directed on some smarter path I can’t predict and don’t even have to know. After all, it’s not about the journey. It’s about the destination.

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